Python Anaconda 与 miniconda

Anaconda vs. miniconda

提问by user288609

In the Anaconda repository, there are two types of installers:

在Anaconda 存储库中，有两种类型的安装程序：

"Anaconda installers" and "Miniconda installers".

“ Anaconda 安装程序”和“ Miniconda 安装程序”。

What are their differences?

它们的区别是什么？

Besides, for an installer file, Anaconda2-4.4.0.1-Linux-ppc64le.sh, what does 2-4.4.0.1stand for?

此外，对于安装程序文件，Anaconda2-4.4.0.1-Linux-ppc64le.sh，这是什么2-4.4.0.1立场？

采纳答案by Y0da

The difference is that miniconda is just shipping the repository management system. So when you install it there is just the management system without packages. Whereas with Anaconda, it is like a distribution with some built in packages.

不同之处在于 miniconda 只是提供存储库管理系统。因此，当您安装它时，只有没有软件包的管理系统。而对于 Anaconda，它就像一个带有一些内置包的发行版。

Like with any Linux distribution, there are some releases which bundles lots of updates for the included packages. That is why there is a difference in version numbering. If you only decide to upgrade Anaconda, you are updating a whole system.

与任何 Linux 发行版一样，有一些发行版为包含的软件包捆绑了大量更新。这就是版本编号不同的原因。如果您只决定升级 Anaconda，那么您就是在更新整个系统。

回答by Alexander

Per the original docs (link is now dead):

根据原始文档（链接现已失效）：

Choose Anaconda if you:

如果您符合以下条件，请选择 Anaconda：

• Are new to conda or Python
• Like the convenience of having Python and over 150 scientific packages automatically installed at once
• Have the time and disk space (a few minutes and 3 GB), and/or
• Don't want to install each of the packages you want to use individually.

• 刚接触 conda 或 Python
• 喜欢一次自动安装 Python 和 150 多个科学软件包的便利
• 有时间和磁盘空间（几分钟和 3 GB），和/或
• 不想安装要单独使用的每个软件包。

Choose Miniconda if you:

如果您符合以下条件，请选择 Miniconda：

• Do not mind installing each of the packages you want to use individually.
• Do not have time or disk space to install over 150 packages at once, and/or
• Just want fast access to Python and the conda commands, and wish to sort out the other programs later.

• 不要介意安装要单独使用的每个软件包。
• 没有时间或磁盘空间一次安装超过 150 个软件包，和/或
• 只是想快速访问 Python 和 conda 命令，并希望稍后整理其他程序。

I use Miniconda myself. Anaconda is bloated. Many of the packages are never used and could still be easily installed if and when needed.

我自己使用 Miniconda。蟒蛇是臃肿的。许多软件包从未使用过，如果需要，仍然可以轻松安装。

Note that Condais the package manager (e.g. conda listdisplays all installed packages in the environment), whereas Anaconda and Miniconda are distributions. A software distribution is a collection of packages, pre-built and pre-configured, that can be installed and used on a system. A package manager is a tool that automates the process of installing, updating, and removing packages.

请注意，Conda是包管理器（例如，conda list显示环境中所有已安装的包），而 Anaconda 和 Miniconda 是发行版。软件发行版是一组预构建和预配置的软件包，可以在系统上安装和使用。包管理器是一种工具，可自动执行安装、更新和删除包的过程。

Anaconda is a full distribution of the central software in the PyData ecosystem, and includes Python itself along with the binaries for several hundred third-party open-source projects. Miniconda is essentially an installer for an empty conda environment, containing only Conda, its dependencies, and Python. Source.

Anaconda 是 PyData 生态系统中核心软件的完整发行版，包括 Python 本身以及数百个第三方开源项目的二进制文件。Miniconda 本质上是一个空 conda 环境的安装程序，只包含 Conda、它的依赖项和 Python。 来源。

Once Conda is installed, you can then install whatever package you need from scratch along with any desired version of Python.

一旦安装了 Conda，您就可以从头开始安装您需要的任何软件包以及任何所需的 Python 版本。

2-4.4.0.1is the version number for your Anaconda installation package. Strangely, it is not listed in their Old Package Lists.

2-4.4.0.1是 Anaconda 安装包的版本号。奇怪的是，它没有列在他们的Old Package Lists 中。

In April 2016, the Anaconda versioning jumped from 2.5 to 4.0 in order to avoid confusion with Python versions 2 & 3. Version 4.0 included the Anaconda Navigator.

2016 年 4 月，Anaconda 版本控制从 2.5 跃升至 4.0，以避免与 Python 版本 2 和 3 混淆。版本 4.0 包含 Anaconda Navigator。

Release notes for subsequent versions can be found here.

可以在此处找到后续版本的发行说明。

回答by Bonifacio2

Miniconda gives you the Python interpreter itself, along with a command-line tool called conda which operates as a cross-platform package manager geared toward Python packages, similar in spirit to the apt or yum tools that Linux users might be familiar with.

Miniconda 为您提供 Python 解释器本身，以及一个名为 conda 的命令行工具，该工具作为面向 Python 包的跨平台包管理器运行，其精神类似于 Linux 用户可能熟悉的 apt 或 yum 工具。

Anaconda includes both Python and conda, and additionally bundles a suite of other pre-installed packages geared toward scientific computing. Because of the size of this bundle, expect the installation to consume several gigabytes of disk space.

Anaconda 包括 Python 和 conda，另外还捆绑了一套其他面向科学计算的预安装包。由于此捆绑包的大小，预计安装将消耗数 GB 的磁盘空间。

Source: Jake VanderPlas's Python Data Science Handbook

来源：Jake VanderPlas 的Python 数据科学手册

回答by Simba

Brief

简短的

condais both a command line tool, and a python package.

conda既是一个命令行工具，又是一个 python 包。

Miniconda installer = Python + conda

Miniconda 安装程序 = Python + conda

Anaconda installer = Python + conda+ meta packageanaconda

Anaconda 安装程序 = Python conda++元包anaconda

meta Python pkg anaconda= about 160 Python pkgs for daily use in data science

meta Python pkg anaconda= 大约 160 个Python pkg，用于数据科学的日常使用

Anaconda installer = Miniconda installer + conda install anaconda

Anaconda 安装程序 = Miniconda 安装程序 + conda install anaconda

Detail

细节

1. condais a python manager and an environment manager, which makes it possible to

   • install package with conda install flake8
   • create an environment with any version of Python with conda create -n myenv python=3.6

2. Miniconda installer = Python + conda

   conda, the package manager and environment manager, is a Python package. So Python is installed. Cause conda distribute Python interpreter with its own libraries/dependencies but not the existing ones on your operating system, other minimal dependencies like openssl, ncurses, sqlite, etc are installed as well.

   Basically, Miniconda is just condaand its minimal dependencies. And the environment where condais installed is the "base" environment, which is previously called "root" environment.

3. Anaconda installer = Python + conda+ meta package anaconda

4. meta Python package anaconda= about 160 Python pkgs for daily use in data science

   Meta packages, are packages that do NOT contain actual softwares and simply depend on other packages to be installed.

   Download an anacondameta package from Anaconda Cloudand extract the content from it. The actual 160+ packages to be installed are listed in info/recipe/meta.yaml.

   package:
       name: anaconda
       version: '2019.07'
   build:
       ignore_run_exports:
           - '*'
       number: '0'
       pin_depends: strict
       string: py36_0
   requirements:
       build:
           - python 3.6.8 haf84260_0
       is_meta_pkg:
           - true
       run:
           - alabaster 0.7.12 py36_0
           - anaconda-client 1.7.2 py36_0
           - anaconda-project 0.8.3 py_0
           # ...
           - beautifulsoup4 4.7.1 py36_1
           # ...
           - curl 7.65.2 ha441bb4_0
           # ...
           - hdf5 1.10.4 hfa1e0ec_0
           # ...
           - ipykernel 5.1.1 py36h39e3cac_0
           - ipython 7.6.1 py36h39e3cac_0
           - ipython_genutils 0.2.0 py36h241746c_0
           - ipywidgets 7.5.0 py_0
           # ...
           - jupyter 1.0.0 py36_7
           - jupyter_client 5.3.1 py_0
           - jupyter_console 6.0.0 py36_0
           - jupyter_core 4.5.0 py_0
           - jupyterlab 1.0.2 py36hf63ae98_0
           - jupyterlab_server 1.0.0 py_0
           # ...
           - matplotlib 3.1.0 py36h54f8f79_0
           # ...
           - mkl 2019.4 233
           - mkl-service 2.0.2 py36h1de35cc_0
           - mkl_fft 1.0.12 py36h5e564d8_0
           - mkl_random 1.0.2 py36h27c97d8_0
           # ...
           - nltk 3.4.4 py36_0
           # ...
           - numpy 1.16.4 py36hacdab7b_0
           - numpy-base 1.16.4 py36h6575580_0
           - numpydoc 0.9.1 py_0
           # ...
           - pandas 0.24.2 py36h0a44026_0
           - pandoc 2.2.3.2 0
           # ...
           - pillow 6.1.0 py36hb68e598_0
           # ...
           - pyqt 5.9.2 py36h655552a_2
           # ...
           - qt 5.9.7 h468cd18_1
           - qtawesome 0.5.7 py36_1
           - qtconsole 4.5.1 py_0
           - qtpy 1.8.0 py_0
           # ...
           - requests 2.22.0 py36_0
           # ...
           - sphinx 2.1.2 py_0
           - sphinxcontrib 1.0 py36_1
           - sphinxcontrib-applehelp 1.0.1 py_0
           - sphinxcontrib-devhelp 1.0.1 py_0
           - sphinxcontrib-htmlhelp 1.0.2 py_0
           - sphinxcontrib-jsmath 1.0.1 py_0
           - sphinxcontrib-qthelp 1.0.2 py_0
           - sphinxcontrib-serializinghtml 1.1.3 py_0
           - sphinxcontrib-websupport 1.1.2 py_0
           - spyder 3.3.6 py36_0
           - spyder-kernels 0.5.1 py36_0
           # ...
   

   The pre-installed packages from meta pkg anacondaare mainly for web scraping and data science. Like requests, beautifulsoup, numpy, nltk, etc.

   If you have a Miniconda installed, conda install anacondawill make it same as an Anaconda installation, except that the installation folder names are different.

5. Miniconda2 v.s. Miniconda. Anaconda2 v.s. Anaconda.

   2means the bundled Python interpreter for condain the "base" environment is Python 2, but not Python 3.

1. conda是一个 python 管理器和一个环境管理器，这使得

   • 安装包 conda install flake8
   • 使用任何版本的 Python 创建一个环境 conda create -n myenv python=3.6

2. Miniconda 安装程序 = Python + conda

   conda，包管理器和环境管理器，是一个 Python 包。这样Python就安装好了。原因畅达分发Python解释器与它自己的库/依存关系，但不是你的操作系统上现有的其他最小的相关喜欢openssl，ncurses，sqlite，等还安装了。

   基本上，Miniconda 只是conda它的最小依赖项。conda安装的环境是“基础”环境，以前称为“根”环境。

3. Anaconda 安装程序 = Python conda++ 元包anaconda

4. 元 Python 包anaconda= 大约 160 个Python 包，用于数据科学的日常使用

   元软件包，是不包含实际软件的软件包，仅依赖于要安装的其他软件包。

   anaconda从Anaconda Cloud下载元数据包并从中提取内容。要安装的实际 160 多个软件包列在info/recipe/meta.yaml.

   package:
       name: anaconda
       version: '2019.07'
   build:
       ignore_run_exports:
           - '*'
       number: '0'
       pin_depends: strict
       string: py36_0
   requirements:
       build:
           - python 3.6.8 haf84260_0
       is_meta_pkg:
           - true
       run:
           - alabaster 0.7.12 py36_0
           - anaconda-client 1.7.2 py36_0
           - anaconda-project 0.8.3 py_0
           # ...
           - beautifulsoup4 4.7.1 py36_1
           # ...
           - curl 7.65.2 ha441bb4_0
           # ...
           - hdf5 1.10.4 hfa1e0ec_0
           # ...
           - ipykernel 5.1.1 py36h39e3cac_0
           - ipython 7.6.1 py36h39e3cac_0
           - ipython_genutils 0.2.0 py36h241746c_0
           - ipywidgets 7.5.0 py_0
           # ...
           - jupyter 1.0.0 py36_7
           - jupyter_client 5.3.1 py_0
           - jupyter_console 6.0.0 py36_0
           - jupyter_core 4.5.0 py_0
           - jupyterlab 1.0.2 py36hf63ae98_0
           - jupyterlab_server 1.0.0 py_0
           # ...
           - matplotlib 3.1.0 py36h54f8f79_0
           # ...
           - mkl 2019.4 233
           - mkl-service 2.0.2 py36h1de35cc_0
           - mkl_fft 1.0.12 py36h5e564d8_0
           - mkl_random 1.0.2 py36h27c97d8_0
           # ...
           - nltk 3.4.4 py36_0
           # ...
           - numpy 1.16.4 py36hacdab7b_0
           - numpy-base 1.16.4 py36h6575580_0
           - numpydoc 0.9.1 py_0
           # ...
           - pandas 0.24.2 py36h0a44026_0
           - pandoc 2.2.3.2 0
           # ...
           - pillow 6.1.0 py36hb68e598_0
           # ...
           - pyqt 5.9.2 py36h655552a_2
           # ...
           - qt 5.9.7 h468cd18_1
           - qtawesome 0.5.7 py36_1
           - qtconsole 4.5.1 py_0
           - qtpy 1.8.0 py_0
           # ...
           - requests 2.22.0 py36_0
           # ...
           - sphinx 2.1.2 py_0
           - sphinxcontrib 1.0 py36_1
           - sphinxcontrib-applehelp 1.0.1 py_0
           - sphinxcontrib-devhelp 1.0.1 py_0
           - sphinxcontrib-htmlhelp 1.0.2 py_0
           - sphinxcontrib-jsmath 1.0.1 py_0
           - sphinxcontrib-qthelp 1.0.2 py_0
           - sphinxcontrib-serializinghtml 1.1.3 py_0
           - sphinxcontrib-websupport 1.1.2 py_0
           - spyder 3.3.6 py36_0
           - spyder-kernels 0.5.1 py36_0
           # ...
   

   来自 meta pkg 的预安装包anaconda主要用于网络抓取和数据科学。像requests，beautifulsoup，numpy，nltk，等。

   如果您安装了 Miniconda，conda install anaconda将使其与 Anaconda 安装相同，只是安装文件夹名称不同。

5. Miniconda2 与 Miniconda。Anaconda2 与 Anaconda。

   2意味着conda在“基础”环境中捆绑的 Python 解释器是 Python 2，而不是 Python 3。

回答by Rory Daulton

The 2in Anaconda2means that the main version of Python will be 2.x rather than the 3.x installed in Anaconda3. The current release has Python 2.7.13.

在2中Anaconda2，这意味着Python的主要版本将2.x的，而不是安装在3.x Anaconda3。当前版本有 Python 2.7.13。

The 4.4.0.1is the version number of Anaconda. The current advertised version is 4.4.0and I assume the .1is a minor release or for other similar use. The Windows releases, which I use, just say 4.4.0in the file name.

该4.4.0.1是蟒蛇的版本号。当前宣传的版本是4.4.0，我认为它.1是次要版本或用于其他类似用途。我使用的 Windows 版本只是4.4.0在文件名中说明。

Others have now explained the difference between Anaconda and Miniconda, so I'll skip that.

其他人现在已经解释了 Anaconda 和 Miniconda 之间的区别，所以我将跳过它。

回答by Gray

Anaconda is a very large installation ~ 2 GB and is most useful for those users who are not familiar with installing modules or packages with other package managers.

Anaconda 是一个非常大的安装 ~ 2 GB，对于那些不熟悉使用其他包管理器安装模块或包的用户最有用。

Anaconda seems to be promoting itself as the official package manager of Jupyter. It's not. Anaconda bundles Jupyter, R, python, and many packages with its installation.

Anaconda 似乎在宣传自己是 Jupyter 的官方包管理器。它不是。Anaconda 捆绑了 Jupyter、R、python 和许多安装包。

Anaconda is not necessary for installing Jupyter Lab or the R kernel. There is plenty of information available elsewhere for installing Jupyter Lab or Notebooks. There is also plenty of information elsewhere for installing R studio. The following shows how to install the R kernel directly from R Studio:

安装 Jupyter Lab 或 R 内核不需要 Anaconda。其他地方有大量信息可用于安装 Jupyter Lab 或 Notebooks。其他地方也有很多关于安装 R studio 的信息。下面显示了如何直接从 R Studio 安装 R 内核：

To install the R kernel, without Anaconda, start R Studio. In the R terminal window enter these three commands:

要在没有 Anaconda 的情况下安装 R 内核，请启动 R Studio。在 R 终端窗口中输入以下三个命令：

install.packages("devtools")
devtools::install_github("IRkernel/IRkernel")
IRkernel::installspec()

Done. The next time Jupyter is opened, the R kernel will be available and available.

完毕。下次打开 Jupyter 时，R 内核将可用且可用。

回答by Adhiraj Chattopadhyay

Both Anaconda and miniconda use the condapackage manager. The chief differece between between Anacondaand miniconda,however,is that

无论蟒蛇和miniconda使用畅达包管理器。然而，Anaconda和miniconda之间的主要区别在于

The Anaconda distribution comes pre-loaded with all the packages while the miniconda distribution is just the management system without any pre-loaded packages. If one uses miniconda, one has to download individual packages and libraries separately.

Anaconda 发行版预装了所有软件包，而 miniconda 发行版只是没有任何预装软件包的管理系统。如果使用 miniconda，则必须分别下载单独的软件包和库。

I personally use Anaconda distribution as I dont really have to worry much about individual package installations.

我个人使用 Anaconda 发行版，因为我真的不必担心单个软件包的安装。

A disadvantage of miniconda is that installing each individual package can take a long amount of time. Compared to that installing and using Anaconda takes a lot less time.

miniconda的一个缺点是，安装每个单个包可利用长量时间。与安装和使用 Anaconda 相比，花费的时间要少得多。

However, there are some packages in anaconda (QtConsole, Glueviz,Orange3) that I have never had to use. I dont even know their purpose. So a disadvantage of anaconda is that it occupies more space than needed.

但是，anaconda 中有一些我从未使用过的软件包（QtConsole、Glueviz、Orange3）。我什至不知道他们的目的。所以 anaconda 的一个缺点是它占用的空间比需要的多。